Method for measuring critical dimensions of a metal mask

Abstract

The application provides a metal mask key dimension measurement method. The method acquires a first measurement image in a state that a backlight source is turned on and there is no test sample on a glass stage. Intrinsic compensation values of a measurement device are calculated according to the first measurement image, which is equivalent to quantifying the illumination non-uniformity of the backlight source and the glass stage through the intrinsic compensation values, thereby providing basic data for subsequent compensation based on the intrinsic error of the device. In the application, the key dimension measurement value of the test sample is compensated according to the relationship between the gray scale value and the interval size, the influence of the measurement device is eliminated, and the measurement accuracy and reliability are improved.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a method for measuring key dimensions of a metal mask. Background Art

[0002] Masks primarily serve as pattern transfer masters and are typically customizable. Masks are categorized as photomasks (light masks) and metal masks (shadow masks). Photomasks, made of high-purity quartz glass, are primarily used in the photolithography process to create circuits. Fine metal masks (FMMs) are key components in OLED display manufacturing, used for the precise deposition of organic materials to form pixel patterns.

[0003] Total Pitch and Critical Dimension (TPCD) metrology equipment is used to measure critical dimensions during the FMM manufacturing process. The TPCD measurement system utilizes a stripe backlight design, powered by an LED array. Due to the physical properties of LED arrays, LED luminous intensity varies across different areas, resulting in poor overall brightness uniformity.

[0004] In addition, the glass stage of the TPCD measurement equipment has differences in flatness in actual use, further exacerbating the uneven illumination when measuring products in different areas.

[0005] The above two types of illumination non-uniformity directly affect the CD (critical dimension) measurement results of TPCD measurement equipment, resulting in inherent differences in the CD measurement process, which has a significant impact on the measurement accuracy of critical dimensions in the FMM manufacturing process. Summary of the Invention

[0006] The present application provides a method for measuring the critical dimensions of a metal mask. By analyzing the measurement image when there is no sample to be tested, the brightness distribution information of the backlight source and the glass carrier is extracted, and a relationship between the grayscale value and the spacing size is established, thereby compensating for the critical dimensions of the sample to be tested, and then obtaining the corrected values ​​of the critical dimensions of the metal mask at different test points.

[0007] The present invention aims to provide a method for measuring the critical dimension of a metal mask, which is applied to a device for measuring the critical dimension of a metal mask, wherein the metal mask has a first surface and a second surface, each of which has a plurality of first holes and a plurality of second holes spaced apart from each other. The critical dimension is the minimum opening dimension at the intersection of the first holes and the second holes, and the method comprises the following steps:

[0008] S01, when the backlight is on and there is no test sample on the glass stage, obtain a first measurement image, and calculate the inherent compensation value of the critical dimension of the measurement device at different preset test points based on the relationship between grayscale value and spacing size , A is the total number of all preset test points, a≤A, A and a are both positive integers;

[0009] S02, with the backlight on and the sample to be tested placed on the glass stage, obtain a second measurement image, as well as the position coordinates of the reference point and the bth test point, where B is the total number of all test points, b≤B, B and b are both positive integers, and B<A;

[0010] S03, determining whether the shape and size of the holes of the metal mask reflected by the relationship between the grayscale value and the pitch size used in S01 are consistent with the shape and size of the holes of the sample to be tested described in S02;

[0011] S04, when the shape and size of the hole are consistent, or when the shape of the hole is inconsistent or both the shape and size of the hole are inconsistent, use the first correction method for measurement; when the shape of the hole is consistent but the size of the hole is inconsistent, use the second correction method different from the first correction method for measurement.

[0012] In one embodiment, the first correction method is: finding the inherent compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the bth test point in the first measurement image , and according to Generate the correction value of the critical dimension of the metal mask at the bth test point ,in It is the key size value of the standard position obtained through standard image testing.

[0013] In one embodiment, the second correction method is:

[0014] If the shapes of the holes are consistent but the sizes of the holes are inconsistent, then find the inherent compensation value of the critical dimension of the preset test point corresponding to the position coordinates of the reference point in the first measurement image. ;

[0015] Find the intrinsic compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the bth test point in the first measurement image ;

[0016] Calculate the difference between the intrinsic compensation value of the critical dimension of the bth test point and the reference point in the second measurement image , , and according to Generate the correction value of the critical dimension of the metal mask at the bth test point .

[0017] In one embodiment, S01, a first measurement image is acquired, and the inherent compensation value of the critical dimension of the measurement device at different preset test points is calculated by combining the relationship between the grayscale value and the spacing size. , the steps include:

[0018] S011, capturing one first measurement image each time the backlight source moves, obtaining a total of A first measurement images, each of which acquires image information of a preset test point;

[0019] S012: Obtain the average grayscale value of the ath first measurement image. The average grayscale value of the a-th first measurement image is substituted into the relationship between the grayscale value and the spacing size to determine the inherent compensation value of the preset test point where the a-th first measurement image is located. , the value of a is 1, 2, 3...A.

[0020] In one embodiment, S01, a first measurement image is acquired, and the inherent compensation value of the critical dimension of the measurement device at different preset test points is calculated by combining the relationship between the grayscale value and the spacing size. , the steps include:

[0021] S0111, capturing one first measurement image each time the backlight source moves, obtaining a total of A first measurement images, each first measurement image obtaining image information of a preset test point;

[0022] S0112, respectively obtain the average grayscale value of A pieces of the first measurement image , , ...... , and select the mode value of the average grayscale value As a benchmark value;

[0023] S0113, the average grayscale value of the ath first measurement image With the mode value The difference is brought into the relationship between the grayscale value and the spacing size to determine the inherent compensation value of the preset test point where the ath first measurement image is located. , the value of a is 1, 2, 3...A.

[0024] In one embodiment, the average grayscale value of the ath first measurement image The calculation methods include:

[0025] S01a, deriving a plurality of pixel regions based on the critical dimension and the designed aperture spacing of the test sample to be compensated, wherein the first pixel region is a first circular region formed with the origin of the first measurement image as the center and the sum of 1.5 times the critical dimension and 2 times the designed aperture spacing as the radius; the second pixel region is an annular region formed by subtracting the first circular region from the second circular region formed with the origin of the first measurement image as the center and the sum of 2.5 times the critical dimension and 3 times the designed aperture spacing as the radius; and the third pixel region is the pixel region remaining after subtracting the first pixel region and the second pixel region from all regions of the a-th first measurement image;

[0026] S01b, the grayscale weight of the first pixel region is 100%, the grayscale weight of the second pixel region is 95%, and the grayscale weight of the third pixel region is 80%;

[0027] S01c, calculating the average grayscale value of the ath first measurement image according to the following formula :

[0028] ,in, is the average grayscale value of the first pixel area, is the average grayscale value of the second pixel area, is the average grayscale value of the third pixel area.

[0029] In one embodiment, the step of establishing a relationship between grayscale values ​​and spacing sizes includes:

[0030] S10, with the backlight source turned on and fixedly positioned at the center of the glass stage and a standard sample placed on the glass stage, determining a reference point (0, 0) and acquiring a standard image of the reference point;

[0031] S20, selecting a plurality of processing ranges consistent with the standard hole size from the standard image, and performing image processing on the image information within each of the processing ranges to obtain M processed images, forming a total of M data groups (Xi, Yi);

[0032] The image processing process includes setting different grayscale thresholds between 0 and 255, observing whether the boundary outline of the standard hole can be formed within the processing range, and if the boundary outline of the standard hole is formed under a certain grayscale threshold, then the grayscale value Xi of the processing range under the grayscale threshold and the measured value Yi of the critical dimension of the standard hole are recorded, wherein the measured value Yi of the critical dimension of the standard hole is obtained by calculating the boundary outline.

[0033] S30 , performing data fitting on the M data groups (Xi, Yi) to obtain a relationship between the grayscale value X and the standard hole critical dimension Y.

[0034] In one embodiment, in step S30, the least square method is used to perform data fitting on the multiple data sets (Xi, Yi), including the following steps:

[0035] S301, providing M data sets (Xi, Yi), and assuming that the values ​​in the M data sets (Xi, Yi) satisfy the linear model: , k is the slope, b is the intercept, is a random error;

[0036] S302, using the following formulas (1), (2), and (3), under the premise of minimizing the residual sum of squares (RSS), calculate the slope k and the intercept b:

[0037] Formula (1);

[0038] Formula (2);

[0039] Formula (3);

[0040] S303, calculate the coefficient R using the following formula (4) and formula (5): 2 ,like , then determine that the relationship between the grayscale value and the spacing size satisfies the linear model Y=kX+b,

[0041] Formula (4);

[0042] Formula (5).

[0043] In one embodiment, in step S303, if , then assume that the values ​​in the M data sets (Xi, Yi) satisfy the quadratic model: , where d1 is the coefficient of the quadratic term, d2 is the coefficient of the linear term, and e is a constant. is a random error;

[0044] Solve d1, d2, and e through calculations and perform model verification.

[0045] In one embodiment, the second measurement image acquired in S02 is an image of the first surface as an upper surface;

[0046] The standard image acquired in S10 is an image in which the first surface is an upper surface;

[0047] The method further includes: a step of verifying the relationship between the grayscale value and the spacing size, including:

[0048] S100, with the backlight source turned on and fixedly positioned at the center of the glass stage, a standard sample placed on the glass stage, and the second surface being the upper surface, determining a reference verification point (0, 0) and acquiring a standard verification image of the reference verification point;

[0049] S200, selecting multiple verification processing ranges consistent with the minimum opening size from the standard verification image, and performing image processing on the image information within each verification processing range to obtain N processed images, forming a total of N data groups (Xj, Yj);

[0050] Among them, the image processing process includes setting different grayscale thresholds (binarized threshold parameters) between 0 and 255, observing whether the boundary contour of the minimum opening size can be formed within the verification processing range, and if the boundary contour of the minimum opening size is formed under a certain grayscale threshold, then the grayscale value Xj of the verification processing range under the grayscale threshold and the measured value Yj of the minimum opening size are recorded, wherein the measured value Yj of the minimum opening size is obtained by calculating the boundary contour.

[0051] S300 , performing data fitting on the N data groups (Xj, Yj) to obtain a relationship between the grayscale value X and the minimum opening size Y;

[0052] S400: If the “relationship between grayscale value X and minimum opening size Y” and the “relationship between grayscale value and spacing size” are the same function model, and the difference in grayscale value coefficients is less than 0.01, then the verification of the relationship between grayscale value and spacing size is completed.

[0053] In one embodiment, the backlight width is , the backlight source is The measurement image is moved at a frequency of mm / time, and the center of the measurement image obtained in each shooting coincides with the center of the backlight source.

[0054] The present invention has at least the following advantages or beneficial effects:

[0055] In this application, a first measurement image is acquired with the backlight on and no test sample on the glass stage. Calculating the inherent compensation value of the measurement device based on this first measurement image quantifies the illumination nonuniformity of the backlight and glass stage using the inherent compensation value, providing basic data for subsequent compensation based on the inherent errors of the device. Based on the relationship between grayscale value and pitch size, compensation is applied to the critical dimensional measurements of the test sample, eliminating the influence of the measurement device and improving measurement accuracy and reliability.

[0056] In this application, by analyzing measurement images without product, we extract the brightness distribution information of the light source and glass stage, accurately calculating the impact of the measurement equipment on the key dimension measurement value, thereby eliminating measurement deviations caused by illumination non-uniformity. In this application, image processing technology is used to quickly obtain brightness distribution information for each area, eliminating the need for additional measurement equipment, reducing measurement cost and time.

[0057] In this application, the relationship between grayscale value and spacing size is used to compensate for the measurement results, which significantly improves the reliability and consistency of the measurement results. By determining the inherent compensation value of different preset test points , which is absolute and can clearly define the inherent compensation value of each preset test point, making it easier to apply in the subsequent compensation process.

[0058] In this application, due to the special structural design of the metal mask (the presence of a first hole and a second hole), when the backlight illuminates the second surface (the backside) of the metal mask, the propagation of light changes. To avoid the unevenness of the light when the backlight illuminates the metal mask, which may affect the accuracy of the grayscale value, practical experience has shown that, according to this embodiment, the first measurement image is configured as multiple pixel regions, and different grayscale weights are assigned to different pixel regions. This makes the calculated grayscale value of the a-th preset test point closer to the actual captured value of the second measurement image (the second measurement image is the image captured after being affected by the hole structure of the metal mask).

[0059] In this application, for different types of metal masks (with different hole patterns / different sizes), different hole patterns have different critical dimensions, and different grayscale value and spacing size relationship equations are fitted. Based on algorithms and a large amount of data measurement and processing, the relationship between grayscale value and spacing size is established to achieve accurate and quantitative evaluation of the relationship between grayscale value and critical dimension. Coefficient R 2 The closer it is to 1, the more accurate the fitting model is. , then assume that the values ​​in the M data groups (Xi, Yi) satisfy the quadratic model, or combine the data characteristics to determine whether it is necessary to verify the polynomial fitting model, fractional fitting model, piecewise fitting model, etc.

[0060] In this application, a verification method for the relationship between grayscale value and spacing size is provided. The verified relationship is more accurate, and the value of the critical dimension calculated by the relationship is more real and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0062] Figure 1 A schematic diagram of a process for measuring critical dimensions of a metal mask provided by an embodiment of the present invention;

[0063] Figure 2 A schematic cross-sectional view of a portion of a metal mask provided by an embodiment of the present invention;

[0064] Figure 3 A schematic diagram of a first measurement image provided by an embodiment of the present invention;

[0065] Figure 4 A schematic diagram of a second measurement image provided by an embodiment of the present invention;

[0066] Figure 5a 、 Figure 5b 、 Figure 5c 、 Figure 5d 、 Figure 5e They are respectively the shapes of different types of holes in different metal mask plates in the embodiments of the present application;

[0067] Figure 6a This is a schematic diagram of the structure when capturing an image of a preset test point 1 in an embodiment of the present application;

[0068] Figure 6b This is a schematic diagram of the structure when capturing an image of the preset test point 2 in an embodiment of the present application;

[0069] Figure 6c This is a schematic diagram of the structure when capturing an image of a preset test point A in an embodiment of the present application;

[0070] Figure 7a The first measurement image with the position coordinates of (0, 159) in the embodiment of the present application;

[0071] Figure 7b is a grayscale value distribution diagram of the first measurement image in the embodiment of the present application;

[0072] Figure 8a This is a schematic diagram of dividing the a-th first measurement image into three pixel areas in an embodiment of the present application;

[0073] Figure 8b The division logic of three pixel regions is illustrated in the second measurement image in the embodiment of the present application;

[0074] Figure 8c The cross-sectional view during the image capture process on both sides of the embodiment of the present application illustrates the division logic of the three pixel areas;

[0075] Figure 9a The grayscale image of the standard hole formed when the grayscale threshold is equal to 92 in the embodiment of the present application;

[0076] Figure 9b The grayscale image of the standard hole formed when the grayscale threshold is equal to 112 in the embodiment of the present application;

[0077] Figure 9c The grayscale image of the standard hole formed when the grayscale threshold is equal to 122 in the embodiment of the present application;

[0078] Figure 9d The grayscale image of the standard hole formed when the grayscale threshold is equal to 132 in the embodiment of the present application;

[0079] Figure 10a In the embodiment of the present application, the second measurement image acquired in S02 is an image of the first surface as the upper surface;

[0080] Figure 10b In the embodiment of the present application, the image obtained in S100 is an image of the second surface being the upper surface;

[0081] Figure 11 A schematic diagram of a critical dimension measurement device for a metal mask in an embodiment of the present application;

[0082] Figure 12 This is a detailed structural diagram of the backlight source in the embodiment of this application;

[0083] Figure 13 Grayscale data of the flatness of the glass stage in the embodiment of this application;

[0084] Figure 14 Grayscale distribution trend diagram of all preset test points in the embodiment of this application;

[0085] Figure 15 A distribution diagram of actual test points in the second two-sided image in an embodiment of the present application;

[0086] Figure 16a The relationship between the two grayscale values ​​and the spacing size obtained by fitting the first hole type in the embodiment of the present application;

[0087] Figure 16b The relationship between the two grayscale values ​​and the spacing size obtained by fitting the second hole type in the embodiment of the present application;

[0088] Figure 16cThe relationship between the two grayscale values ​​and the spacing size obtained by fitting the third hole type in the embodiment of the present application;

[0089] Figure 16d The relationship between the two grayscale values ​​and the spacing size obtained by fitting the fourth hole type in the embodiment of the present application;

[0090] Figure 16e This is the relationship between the two grayscale values ​​and the spacing size fitted by the fifth hole type in the embodiment of the present application.

[0091] icon:

[0092] Light source 10 , glass stage 20 , metal mask 30 : first surface 31 , small hole 311 , second surface 32 , large hole 321 . DETAILED DESCRIPTION

[0093] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0094] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0095] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0096] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" and the like indicate positions or locations based on the positions shown in the accompanying drawings, or the positions or locations in which the inventive product is typically placed when in use. These terms are intended solely to facilitate the description of the present invention and to simplify the description, and are not intended to indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third," etc., are used solely to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0097] Furthermore, terms such as "horizontal" and "vertical" do not necessarily mean that a component must be absolutely horizontal or overhanging, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but rather that it can be slightly tilted.

[0098] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0099] In existing technology, the measurement equipment typically uses an LED array backlight. The uneven brightness of the LED array and variations in the flatness of the glass stage lead to inherent measurement variations in CD measurements using TPCD measurement equipment. Specifically, this illumination unevenness leads to deviations in CD measurement values ​​across different areas, impacting measurement accuracy. Existing technology lacks effective means to measure the illumination level in each area, making it impossible to accurately determine the actual impact of the measurement equipment on the CD measurement results. This inability to accurately determine the impact of the measurement equipment makes it difficult to effectively compensate and correct the measurement results, resulting in low reliability.

[0100] The present application provides a method for measuring the critical dimensions of a metal mask. By analyzing a measurement image without a sample to be tested, the brightness distribution information of the backlight source and the glass carrier is extracted, and a relationship between grayscale value and spacing size is established, thereby compensating for the critical dimension of the sample to be tested and obtaining a corrected value of the critical dimension of the metal mask at the bth test point.

[0101] See also Figure 1 The present application provides a metal mask critical dimension measurement method, which is applied to a metal mask critical dimension measurement device. Figure 2 As shown in FIG, a schematic cross-sectional view of a portion of a metal mask 30 is cut out. The metal mask 30 includes a first surface 31 and a second surface 32. The first surface 31 has a first hole 311 (small hole), and the second surface 32 has a second hole 321 (large hole). The critical dimension is the minimum opening dimension (also called the critical dimension or minimum feature dimension) at the intersection of the first hole 311 and the second hole 321. Figure 2 The CD value shown in . The minimum opening size is the minimum feature size that needs to be strictly controlled during the FMM manufacturing process and directly affects the performance of OLED devices.

[0102] The metal mask critical dimension measurement method involved in this application includes the following steps:

[0103] S01, with the backlight on and no test sample on the glass stage, obtain Figure 3 The first measurement image shown is used to calculate the inherent compensation value of the critical dimension of the measurement equipment at different preset test points by combining the relationship between grayscale value and spacing size. , A is the total number of all preset test points, a≤A, and A and a are both positive integers. The pitch sizes of the different preset test points obtained by substituting the grayscale values ​​of the first measurement image at the different preset test points into the relationship between grayscale value and pitch size are the inherent compensation values ​​of the critical dimensions of the measurement equipment at the different preset test points. In this step, a compensation database of the inherent error of the measuring device can be calculated, or only the inherent error of the measuring device at the corresponding position can be obtained for subsequent compensation according to the detection requirements.

[0104] S02, with the backlight turned on and the sample to be tested placed on the glass stage, obtain the following Figure 4 The second measurement image shown, along with the coordinates of the reference point and the bth test point, is shown. B represents the total number of test points, b≤B, and both B and b are positive integers, where B<A. In this step, the field of view of the first measurement image is a single pre-determined test point. The field of view of the second measurement image is a single test point. The test points in the second measurement image can be determined based on the requirements of the OLED manufacturer.

[0105] S03, determine whether the shape and size of the hole of the metal mask reflected by the relationship between the grayscale value and the spacing size used in S01 are consistent with the shape and size of the hole of the sample to be tested in S02. In this step, the FMM manufacturer can reserve a variety of different relationship formulas. For example, if the relationship between the grayscale value and the spacing size reserved by the FMM manufacturer satisfies the linear relationship, then the shape of the hole of the sample to be tested is as follows: Figure 5a 、 Figure 5b The rounded rectangle (or rectangle) shown and Figure 5c The diamond shown in FIG. satisfies the quadratic relationship, and the shape of the hole of the sample to be tested is as follows: Figure 5d The circle (or ellipse) shown in FIG. satisfies the inverse proportional relationship, and the shape of the hole of the sample to be tested is as follows: Figure 5e The hourglass shape shown. Specifically, Figure 5a 、 Figure 5b 、 Figure 5c 、 Figure 5d 、 Figure 5e As shown in FIG. 1 , different hole shapes in different metal mask plates are shown. Different hole shapes have different critical dimensions, and different relationship equations between grayscale values ​​and spacing dimensions are fitted. Figure 5a and Figure 5b The shapes of the holes are consistent, but the sizes of the holes are inconsistent. Figure 5c 、 Figure 5d and Figure 5e The holes have inconsistent shapes and sizes. Furthermore, the shape and size of the holes in the sample to be tested in S02 are obtained in two ways: first, from the product description of the metal mask. Generally, the shape and size of the holes in the metal mask to be tested, along with other parameters of the metal mask to be tested, are described before critical dimension measurement. Second, the shape of the holes in the metal mask to be tested is observed using the second measurement image obtained in S02, and the size of the holes in the metal mask to be tested is measured using the second measurement image obtained in S02.

[0106] S04: When the hole shapes and sizes are consistent, or when the hole shapes are inconsistent, measurement is performed using a first correction method. When the hole shapes are consistent but the hole sizes are inconsistent, measurement is performed using a second correction method different from the first correction method. In this step, "inconsistent hole shapes" include the following two situations: 1. Inconsistent hole shapes and sizes; 2. Inconsistent hole shapes but consistent hole sizes.

[0107] In this embodiment, a first measurement image is acquired when the backlight source is turned on and there is no test sample on the glass carrier. Calculating the inherent compensation value of the measurement device based on the first measurement image is equivalent to quantifying the illumination non-uniformity of the backlight source and the glass carrier through the inherent compensation value, providing basic data for subsequent compensation based on the inherent error of the device. On the one hand, based on the relationship between the grayscale value and the spacing size, the key dimension measurement value of the test sample is compensated, eliminating the influence of the measurement device and improving the measurement accuracy and reliability. On the one hand, by analyzing the measurement image when there is no product, the brightness distribution information of the light source and the glass carrier is extracted, and the influence of the measurement device on the key dimension measurement value is accurately calculated, thereby eliminating the measurement deviation caused by illumination non-uniformity. On the one hand, the brightness distribution information of each area is quickly acquired by using image processing technology, without the need for additional measurement equipment, reducing measurement cost and time. On the one hand, the measurement results are compensated through the relationship between the grayscale value and the spacing size, significantly improving the reliability and consistency of the measurement results.

[0108] In one embodiment, the first correction method is:

[0109] Find the intrinsic compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the bth test point in the first measurement image , and according to Generate the correction value of the critical dimension of the metal mask at the bth test point ,in is the critical size value of the standard position obtained by the standard image test. In this step, the correction value of the critical size is calculated by absolute calculation. The calculation process can more accurately calculate the inherent compensation value of the critical dimension of the preset test point.

[0110] In one embodiment, the second correction method is:

[0111] Find the intrinsic compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the reference point in the first measurement image ;

[0112] Find the intrinsic compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the bth test point in the first measurement image ;

[0113] Calculate the difference between the intrinsic compensation value of the critical dimension of the bth test point and the reference point in the second measurement image , , and according to Generate the correction value of the critical dimension of the metal mask at the bth test point .

[0114] In this step, the first correction method and the second correction method are parallel schemes. When confirming the relationship between different grayscale values ​​and spacing sizes, the shape and size of the holes in the metal mask are combined to classify different situations, which can simplify the calculation process and improve calculation efficiency.

[0115] In one embodiment, S01, a first measurement image is acquired, and the inherent compensation value of the critical dimension of the measurement device at different preset test points is calculated by combining the relationship between the grayscale value and the spacing size. , the steps include:

[0116] S011, each time the backlight source moves, a first measurement image is captured, and a total of A first measurement images are obtained. Each first measurement image obtains image information of a preset test point. In this step, the image information of the preset test point reflects the information of the backlight source brightness and the glass stage at the preset test point. Figure 6a This is a schematic diagram of the structure when taking an image of the preset test point 1. Figure 6b This is a schematic diagram of the structure when taking an image of the preset test point 2. Figure 6c The schematic diagram shows the structure when capturing an image of the preset test point A.

[0117] S012, obtaining the average grayscale value of the a-th first measurement image The average grayscale value of the a-th first measurement image is used as the grayscale value, and the relationship between the grayscale value and the spacing size is substituted into the relationship between the grayscale value and the spacing size of the preset test point where the a-th first measurement image is located is determined as the inherent compensation value of the preset test point where the a-th first measurement image is located. , the value of a is 1, 2, 3...A. Figure 7a The first measurement image with the coordinates of (0, 159) is shown. Figure 7b is the grayscale value distribution diagram of the first measurement image, and the average grayscale value of the first measurement image is calculated. When it is necessary to remove obvious noise, such as Figure 7b The points with grayscale between 0 and 100 are noise. Figure 7a The "cross" calibration line in .

[0118] In this embodiment, the average grayscale values ​​of different preset test points are obtained respectively, and the relationship between grayscale value and spacing size is respectively introduced to determine the inherent compensation values ​​of different preset test points. , which is absolute and can clearly define the inherent compensation value of each preset test point, making it easier to apply in the subsequent compensation process.

[0119] In one embodiment, S01, a first measurement image is acquired, and the inherent compensation value of the critical dimension of the measurement device at different preset test points is calculated by combining the relationship between the grayscale value and the spacing size. , the steps include:

[0120] S0111, take a first measurement image each time the backlight moves, and obtain A first measurement images in total. Each first measurement image obtains image information of a preset test point. In this step, the image information of the preset test point reflects the information of the backlight brightness and the glass stage at the preset test point. In this step, you can refer to Figure 6a 、 Figure 6b and Figure 6c When photographing each preset test point, the center of the backlight source coincides with the center of the preset test point.

[0121] S0112, respectively obtain the average grayscale value of A first measurement images , , ...... , and select the mode value of the average grayscale value In this step, in a specific practical operation, the mode of the average grayscale values ​​of the A first measurement images can be set as the reference value, so that the test points that need to be compensated can be found more quickly.

[0122] S0113, the average grayscale value of the a-th first measurement image Moderate value The difference between the grayscale value and the spacing size is substituted into the grayscale value and the spacing size of the preset test point where the a-th first measurement image is located is determined to be the inherent compensation value of the preset test point where the a-th first measurement image is located. , the value of a is 1, 2, 3...A.

[0123] In this step, the average grayscale value of the a-th first measurement image is obtained. Moderate value The difference of the key size of the standard hole is calculated by the difference of the first measurement image, which is the inherent compensation value of the preset test point at the ath first measurement image. .

[0124] In the two embodiments of S011-S012 and S0111-S0113 above, the first measurement image is captured / tested when the backlight source is turned on and there is no test sample on the glass stage. Specifically, the backlight source width is d, 100mm-20mm≤d≤100mm+20mm. During actual measurement, the backlight source is moving, and the backlight source is tested by moving at a rate of 10mm per position, that is, an image is collected every time the backlight source moves 10mm. During normal testing, the gap between the hole positions is large, about 120mm. During actual measurement, the spacing of the key dimensions of the standard holes is greater than 100mm. In a specific embodiment, the test points of the second measurement image may include: (420, 0), (300, 0) (180, 0) (0, 0) (-180, 0) (-300, 0) (-420, 0). (420, 32), (300, 32) (180, 32) (0, 32) (-180, 32) (-300, 32), (-420, 32). (420, -32), (300, -32) (180, -32) (0, -32) (-180, -32) (-300, -32) (-420, -32).

[0125] In one embodiment, the average grayscale value of the ath first measurement image The calculation methods include:

[0126] S01a, deriving a plurality of pixel regions according to the critical dimensions of the test sample to be compensated and the designed hole spacing. Figure 8c As shown, the critical dimension (or CD value) is the minimum opening size at the intersection of the first hole 311 and the second hole 321. The design hole spacing is the minimum distance between the two second holes 321. Figure 8a As shown, the ath first measurement image is divided into three pixel areas. Figure 8b As shown, the division logic of the three pixel areas is illustrated in the second measurement image. Figure 8cThe cross-sectional view during the measurement image capture process illustrates the division logic of the three pixel areas (Note: Figure 8c The setting logic is only shown in the figure, and the specific proportional relationship is not limited). Figure 8c Schematic diagram of a light source 10, a glass carrier 20, and a metal mask 30, wherein the total width of the light source 10 is d, and the light source 10 includes three columns of LED dot matrices.

[0127] Specifically, the first pixel area is the first circular area centered at the origin of the first measurement image, with a radius equal to the sum of 1.5 times the critical dimension of the sample to be tested and 2 times the designed hole spacing. The second pixel area is the annular area formed by subtracting the first circular area from the second circular area centered at the origin of the first measurement image, with a radius equal to the sum of 2.5 times the critical dimension of the sample to be tested and 3 times the designed hole spacing. The third pixel area is the pixel area remaining after subtracting the first pixel area and the second pixel area from all areas of the a-th first measurement image.

[0128] S01b, the grayscale weight of the first pixel region is 100%, the grayscale weight of the second pixel region is 95%, and the grayscale weight of the third pixel region is 80%.

[0129] S01c, calculate the average grayscale value of the a-th first measurement image according to the following formula :

[0130] ,in, is the average grayscale value of the first pixel area, is the average grayscale value of the second pixel area, is the average grayscale value of the third pixel area.

[0131] In this embodiment, due to the unique structural design of the metal mask (the presence of the first and second apertures), the propagation of light changes when the backlight illuminates the second surface (backside) of the metal mask. To prevent the unevenness of the backlight when illuminating the metal mask, which could affect the accuracy of the grayscale values, practical experience has demonstrated that, in accordance with this embodiment, by configuring the first measurement image as multiple pixel regions and assigning different grayscale weights to different pixel regions, the calculated grayscale value of the a-th preset test point more closely matches the actual captured value of the second measurement image (the second measurement image is captured after being affected by the aperture structure of the metal mask).

[0132] In one embodiment, the step of establishing a relationship between grayscale values ​​and spacing sizes includes:

[0133] S10, with the backlight turned on and fixed at the center of the glass stage and a standard sample placed on the glass stage, determine the reference point (0, 0) and acquire a standard image of the reference point. In this step, if, for example, 35 standard holes can be observed per shot, the standard hole most centrally located within the field of view is selected as the reference point.

[0134] S20 , multiple processing ranges consistent with the standard hole size are selected from the standard image, and image processing is performed on the image information within each processing range to obtain M processed images, forming a total of M data sets (Xi, Yi). In this step, a processing range is the range of a standard hole.

[0135] The image processing process includes setting multiple grayscale thresholds (binarized threshold parameters) between 0 and 255 with a step size of 1, and observing whether the boundary outline of the standard hole can be formed within the processing range. If the boundary outline of the standard hole is formed under a certain grayscale threshold, the grayscale value Xi of the processing range under the grayscale threshold and the measured value Yi of the key size of the standard hole are recorded, wherein the measured value Yi of the key size of the standard hole is calculated through the boundary outline. Figure 9a 、 Figure 9b 、 Figure 9c and Figure 9d Shown is a grayscale image of a standard hole formed at a certain grayscale threshold. Figure 9a This is the grayscale image of the standard hole formed when the grayscale threshold is equal to 92. The boundary outline of the standard hole can be clearly seen in the figure. Figure 9b This is the grayscale image of the standard hole formed when the grayscale threshold is equal to 112. The boundary outline of the standard hole can be clearly seen in the figure. Figure 9c This is the grayscale image of the standard hole formed when the grayscale threshold is equal to 122. The boundary outline of the standard hole can be clearly seen in the figure. Figure 9d This is the grayscale image of the standard hole formed when the grayscale threshold is equal to 132. The boundary outline of the standard hole cannot be formed in the figure.

[0136] S30 , performing data fitting on the M data sets (Xi, Yi) to obtain a relationship between the grayscale value X and the standard hole critical dimension Y.

[0137] In this embodiment, for metal masks of different models (having different hole patterns / different sizes), different hole patterns have different critical dimensions, and different relationship equations between grayscale values ​​and spacing sizes are fitted.

[0138] The fitting relationship of metal masks of different hole types is different. For example, the relationship between the grayscale value and the critical dimension value of a non-straight-edge hole type satisfies: , .in and They are Figure 5a ( Figure 5b or Figure 5c ) are critical dimensions in two directions as shown.

[0139] In this embodiment, based on an algorithm and a large amount of data measurement and processing, a relationship between grayscale values ​​and spacing dimensions is established, thereby achieving an accurate and quantitative assessment of the relationship between grayscale values ​​and critical dimensions.

[0140] In one embodiment, the least square method is used to perform data fitting on the multiple data sets (Xi, Yi) in step S30, including the following steps:

[0141] S301, providing M data groups (Xi, Yi), and assuming that the values ​​in the M data groups (Xi, Yi) satisfy the linear model: , is the slope, is the intercept, is a random error.

[0142] S302, using the following formulas (1), (2), and (3), under the premise of minimizing the residual sum of squares (RSS), calculate the slope k and the intercept b:

[0143] Formula (1).

[0144] Formula (2).

[0145] Formula (3).

[0146] S303, calculate the coefficient R using the following formula (4) and formula (5): 2 ,like , then the relationship between grayscale value and spacing size satisfies the linear model ,

[0147] Formula (4).

[0148] Formula (5).

[0149] In this embodiment, the coefficient R 2 The closer it is to 1, the more accurate the fitting model is. If the relationship between grayscale value and spacing size satisfies the linear model , then substitute the grayscale value X into the above linear model and output the standard hole critical dimension Y for verification. The verification result can meet the preset error.

[0150] In one embodiment, in step S303, if , then assume that the values ​​in the M data sets (Xi, Yi) satisfy the quadratic model: , where d1 is the coefficient of the quadratic term, d2 is the coefficient of the linear term, and e is a constant. is a random error.

[0151] Solve d1, d2, and e through calculations and perform model verification.

[0152] In this embodiment, based on the data characteristics, it is determined whether it is necessary to verify a polynomial fitting model (quadratic fitting model), a fractional fitting model, a piecewise fitting model, an inverse proportional fitting model, or the like.

[0153] In any of the above embodiments of the present application, Figure 10a As shown, the second measurement image acquired in S02 is an image of the first surface being the top surface. The standard image acquired in S10 is an image of the first surface being the top surface. Acquiring a measurement image of the first surface being the top surface in any of the above-described embodiments of the present application can avoid the impact of the second hole on the critical dimension, establish a more precise relationship between grayscale value and pitch dimension, and calculate a more accurate critical dimension value of the metal mask.

[0154] In one embodiment, the method further includes: a step of verifying the relationship between the grayscale value and the spacing size, including:

[0155] S100, with the backlight source turned on and fixed at the center of the glass stage, a standard sample placed on the glass stage, and the second surface being the upper surface, determine the reference verification point (0, 0) and obtain a standard verification image of the reference verification point. Figure 10b As shown, the image obtained in S100 is an image in which the second surface is the upper surface.

[0156] S200, selecting multiple verification processing ranges consistent with the minimum opening size from the standard verification image, and performing image processing on the image information within each verification processing range to obtain N processed images, forming a total of N data groups (Xj, Yj).

[0157] Among them, the image processing process includes setting different grayscale thresholds (binarized threshold parameters) between 0 and 255, observing and verifying whether the boundary contour of the minimum opening size can be formed within the processing range. If the boundary contour of the minimum opening size is formed under a certain grayscale threshold, the grayscale value Xj of the processing range under the grayscale threshold and the measured value Yj of the minimum opening size are recorded, wherein the measured value Yj of the minimum opening size is calculated through the boundary contour.

[0158] S300 , performing data fitting on N data groups (Xj, Yj) to obtain a relationship between the grayscale value X and the minimum opening size Y.

[0159] At step S400, if the "relationship between grayscale value X and minimum opening size Y" and the "relationship between grayscale value and pitch size" are the same function model, and the difference in grayscale value coefficients is less than 0.01, then the grayscale value and pitch size relationship is verified. If the difference is greater than 0.01, the cause is analyzed and a new grayscale value and pitch size relationship is formed.

[0160] In this embodiment, a method for verifying the relationship between grayscale values ​​and spacing dimensions is provided. The verified relationship is more accurate, and the values ​​of the critical dimensions calculated using the relationship are more realistic and reliable.

[0161] In one embodiment, the backlight width is , the backlight source is The frequency of mm / times is used to move, and the center of the measurement image obtained each time is coincident with the center of the backlight source. Figure 6a As shown, when photographing preset test point 1, the backlight is at the far left. At this time, the light emitted by LEDs 11-26 of the backlight has the greatest impact on preset test point 1. When photographing preset test point 11 (not shown), the backlight is also at the far left. At this time, the light emitted by LEDs 27-43 of the backlight has the greatest impact on preset test point 11. Although the backlight positions are the same when photographing preset test points 1 and 11, the primary light-emitting areas of the backlight LEDs are different.

[0162] In a specific embodiment, the backlight width is 100 mm ± 20 mm, and the backlight moves at a frequency of 10 mm / time. The sizes of the metal mask are 850 mm * 70 mm, 850 mm * 150 mm, 1200 mm * 70 mm, 1200 mm * 150 mm, 1200 mm * 220 mm, and 1200 mm * 310 mm.

[0163] In one embodiment, after the measurement device has been used more than a threshold number of times or for a longer period of time, step S01 is executed once to reacquire the inherent compensation values ​​of the measurement device at different test points. Regularly updating data in this step can prevent brightness decay caused by backlight degradation, which in turn can lead to inaccurate inherent compensation values. Therefore, the first measurement image is not static; data is periodically reacquired, for example, once a month.

[0164] In a specific embodiment, the above metal mask critical dimension measurement method is used, and the following Figure 11 The metal mask critical dimension measurement device shown in the figure does not show the control module in the device. Figure 12 FIG. 1 shows a detailed structural diagram of the backlight source 10 . The backlight source 10 includes a plurality of LED chips arranged in a matrix. Figure 13 Shown is the grayscale data of the glass stage flatness. Figure 13 The color change in the image clearly shows that the surface of the glass carrier is not flat. Figure 14 It is the grayscale distribution trend diagram of all preset test points. Figure 14 The color changes in the image clearly show that the grayscale values ​​of different preset points are significantly different. All preset test points cover the entire surface of the glass stage. Figure 15 is a distribution diagram of actual test points in the second measurement image. Figure 16a The relationship between the two grayscale values ​​and the spacing size fitted for the first hole type; Figure 16b The relationship between the two grayscale values ​​and the spacing size fitted for the second hole type; Figure 16c The relationship between the two grayscale values ​​and the spacing size fitted for the third hole type; Figure 16d The relationship between the two grayscale values ​​and the spacing size fitted for the fourth hole type; Figure 16e This is the relationship between the two grayscale values ​​and the spacing size fitted for the fifth hole type.

[0165] In other embodiments, based on the metal mask critical dimension measurement method described in any of the above embodiments of this application, other types of light sources (such as laser light sources) are used instead of LED array light sources, and brightness uniformity is improved by optimizing the light source design. Using other types of light sources (such as laser light sources) instead of LED array light sources can fundamentally reduce the brightness non-uniformity of the light source and minimize the impact of light source non-uniformity.

[0166] In other embodiments, based on the metal mask critical dimension measurement method described in any of the above embodiments of the present application, a high-precision glass stage is used to reduce flatness variations through improved manufacturing processes. The high-precision glass stage can reduce brightness variations caused by stage unevenness and minimize the impact of light source non-uniformity.

[0167] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring the critical dimension of a metal mask, applied to a device for measuring the critical dimension of a metal mask, wherein the metal mask has a first surface and a second surface, each of which has a plurality of first holes and a plurality of second holes spaced apart from each other. The critical dimension is the minimum opening dimension at the intersection of the first holes and the second holes, characterized in that: The following steps are involved: S01, when the backlight is on and there is no test sample on the glass stage, obtain a first measurement image, and calculate the inherent compensation value of the critical dimension of the measurement device at different preset test points based on the relationship between grayscale value and spacing size , A is the total number of all preset test points, a≤A, A and a are both positive integers; wherein, the spacing dimensions of the different preset test points obtained by substituting the grayscale values ​​of the first measurement image at different preset test points into the relationship between grayscale value and spacing dimension are the inherent compensation values ​​of the critical dimensions of the measurement device at different preset test points ; S02, with the backlight on and the sample to be tested placed on the glass stage, obtain a second measurement image, as well as the position coordinates of the reference point and the bth test point, where B is the total number of all test points, b≤B, B and b are both positive integers, and B<A; S03, determining whether the shape and size of the holes of the metal mask reflected by the relationship between the grayscale value and the pitch size used in S01 are consistent with the shape and size of the holes of the sample to be tested described in S02; S04, when the shape and size of the holes are consistent, or when the shape of the holes is inconsistent, use a first correction method to perform measurement; when the shape of the holes is consistent but the size of the holes is inconsistent, use a second correction method different from the first correction method to perform measurement; The step of establishing the relationship between the grayscale value and the spacing size includes: S10, with the backlight source turned on and fixedly positioned at the center of the glass stage and a standard sample placed on the glass stage, determining a reference point (0, 0) and acquiring a standard image of the reference point; S20, selecting a plurality of processing ranges consistent with the standard hole size from the standard image, and performing image processing on the image information within each of the processing ranges to obtain M processed images, forming a total of M data groups (Xi, Yi); The image processing process includes setting different grayscale thresholds between 0 and 255, observing whether the boundary outline of the standard hole can be formed within the processing range, and if the boundary outline of the standard hole is formed under a certain grayscale threshold, recording the grayscale value Xi of the processing range under the grayscale threshold and the measured value Yi of the critical dimension of the standard hole, wherein the measured value Yi of the critical dimension of the standard hole is calculated through the boundary outline; S30 , performing data fitting on the M data groups (Xi, Yi) to obtain a relationship between the grayscale value X and the standard hole critical dimension Y.

2. The metal mask critical dimension measurement method according to claim 1, wherein: Also includes: The first correction method is: Find the intrinsic compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the bth test point in the first measurement image , and according to Generate the correction value of the critical dimension of the metal mask at the bth test point ,in is the key size value of the standard position obtained through standard image testing; The second correction method is: Find the inherent compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the reference point in the first measurement image ; Find the intrinsic compensation value of the critical dimension of the preset test point corresponding to the position coordinate of the bth test point in the first measurement image ; Calculate the difference between the intrinsic compensation value of the critical dimension of the bth test point and the reference point in the second measurement image , , and according to Generate the correction value of the critical dimension of the metal mask at the bth test point .

3. The metal mask critical dimension measurement method according to claim 2, wherein: S01, obtaining a first measurement image, and calculating the inherent compensation value of the critical dimension of the measurement device at different preset test points by combining the relationship between the grayscale value and the spacing size , the steps include: S011, capturing one first measurement image each time the backlight source moves, obtaining a total of A first measurement images, each of which acquires image information of a preset test point; S012: Obtain the average grayscale value of the ath first measurement image. The average grayscale value of the a-th first measurement image is used as the grayscale value, and the grayscale value and spacing size are substituted into the relationship between the grayscale value and the spacing size, and the spacing size of the preset test point where the a-th first measurement image is located is determined as the inherent compensation value of the preset test point where the a-th first measurement image is located. , the value of a is 1, 2, 3...A.

4. The metal mask critical dimension measurement method according to claim 2, wherein: S01, obtaining a first measurement image, and calculating the inherent compensation value of the critical dimension of the measurement device at different preset test points by combining the relationship between the grayscale value and the spacing size , the steps include: S0111, capturing one first measurement image each time the backlight source moves, obtaining a total of A first measurement images, each first measurement image obtaining image information of a preset test point; S0112, respectively obtain the average grayscale value of A pieces of the first measurement image , , ...... , and select the mode value of the average grayscale value As a benchmark value; S0113, the average grayscale value of the ath first measurement image With the mode value The difference between the grayscale value and the spacing size is substituted into the grayscale value and the spacing size of the preset test point of the a-th first measurement image to determine the inherent compensation value of the preset test point of the a-th first measurement image. , the value of a is 1, 2, 3...A.

5. The metal mask critical dimension measurement method according to claim 2 or 3, characterized in that: The average grayscale value of the a-th first measurement image The calculation methods include: S01a, deriving a plurality of pixel areas based on the critical dimension and the designed hole spacing of the test sample to be compensated, where the designed hole spacing is the minimum distance between two of the second holes, wherein the first pixel area is a first circular area formed with the origin of the first measurement image as the center and a radius equal to the sum of 1.5 times the critical dimension and 2 times the designed hole spacing; the second pixel area is an annular area formed by subtracting the first circular area from the second circular area formed with the origin of the first measurement image as the center and a radius equal to the sum of 2.5 times the critical dimension and 3 times the designed hole spacing; and the third pixel area is the pixel area remaining after subtracting the first pixel area and the second pixel area from all areas of the a-th first measurement image; S01b, the grayscale weight of the first pixel region is 100%, the grayscale weight of the second pixel region is 95%, and the grayscale weight of the third pixel region is 80%; S01c, calculating the average grayscale value of the ath first measurement image according to the following formula : ,in, is the average grayscale value of the first pixel area, is the average grayscale value of the second pixel area, is the average grayscale value of the third pixel area.

6. The metal mask critical dimension measurement method according to claim 5, wherein: In step S30, the least square method is used to perform data fitting on the multiple data sets (Xi, Yi), including the following steps: S301, providing M data sets (Xi, Yi), and assuming that the values ​​in the M data sets (Xi, Yi) satisfy the linear model: , k is the slope, b is the intercept, is a random error; S302, using the following formulas (1), (2), and (3), under the premise of minimizing the residual sum of squares (RSS), calculate the slope k and the intercept b: Formula (1); Formula (2); Formula (3); S303, calculate the coefficient R using the following formula (4) and formula (5): 2 ,like , then it is determined that the relationship between the grayscale value and the spacing size satisfies the linear model , Formula (4); Formula (5).

7. The metal mask critical dimension measurement method according to claim 6, characterized in that: In step S303, if , then assume that the values ​​in the M data sets (Xi, Yi) satisfy the quadratic model: , where d1 is the coefficient of the quadratic term, d2 is the coefficient of the linear term, and e is a constant. is a random error; Solve d1, d2, and e through calculations and perform model verification.

8. The metal mask critical dimension measurement method according to claim 7, wherein: The backlight width is , the backlight source is The measurement image is moved at a frequency of mm / time, and the center of the measurement image obtained in each shooting coincides with the center of the backlight source.

Images